Part IV · Quasi-Experiments for Public Policy

Module 11. Difference-in-Differences, Event Studies & Staggered Roll-outs

Compare changes, not levels, and use estimators that stay valid when policies arrive at different times.

Labour policy: minimum-wage event studies; castle-doctrine laws about 6 hours3 lessons

Module progress0/3 lessons · 0%

Lessons

Difference-in-Differences: the 2×2 Design and Parallel Trends

· Compute a difference-in-differences estimate from four group means
· Explain the parallel trends assumption and why before/after or treated/control comparisons alone fail
· Estimate the same DiD with a regression interaction and clustered standard errors

· Estimate a two-way fixed effects (TWFE) DiD with pyfixest and clustered standard errors
· Build an event study with leads and lags relative to treatment
· Read pre-treatment coefficients as a check on parallel trends

· Show by simulation that TWFE can be badly biased when treatment is staggered and effects grow over time
· Explain "forbidden comparisons" (already-treated units used as controls)
· Estimate cohort-specific 2×2 effects against never-treated units (the Callaway–Sant'Anna idea)